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smolagents CodeAgent

From public sources · Self-ReportedCuratedReference design

Python-first multi-provider agent — minimal 1K-line library, MCP + LangChain tools.

Hugging Face· Introduced Jan 1, 2025· Reference design
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Reference design — not an operated team.

Documented from framework or library docs, a design pattern or a tutorial; no one is known to run this team in production.

The source: Library documentation, not a deployed team.

Documented by AgentCV from public sources — not submitted by this team.

Not claimed by or endorsed by the team or its organization. Metrics are cited only as the sources state them; absent metrics render as [unknown].

Sources: Hugging Face — smolagents docs (huggingface.co)

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Recent activity

Version cuts and proof, newest first — the living track record.

  1. Artifact · smolagents CodeAgent documented in Hugging Face docs · 1y ago

Spec sheet

The benchmark fields — designed for comparison across teams.

Topology
Solo + Tools
Agent count
1
Platform
smolagents (Python)
Runs on
smolagents (Python)
Industries
software-deliveryresearchdata-extraction
Task kinds
code-executiontool-usemulti-agent-orchestration
Trust tier
From public sources · Self-Reported
Proof entries
1

Topology & roster

Solo + Tools

Solo-plus-tools (single agent) or hub-and-spoke (multi-agent). CodeAgent primary; can orchestrate ToolCallingAgents as subagents. Each subagent is called as a tool by the coordinator agent. Supports ManagedAgent wrapper for delegating to specialized sub-agents.

System wiring

Typical Solo + Tools layout — schematic, not verified wiring
Typical role-level schematic — not verified wiringdirectswrites towrites toHuman operatorHumanoperatorHUMANGATEAgentAgentBUILDERTool ATool ARESOURCETool BTool BRESOURCE
Node details

Typical Solo + Tools layout — schematic, not verified wiring

HumanHuman operatorHuman gate
Tool
Human operator
Autonomy
Human-gated
Sends
  • directs → Agent
BuilderAgent
Tool
Agent
Autonomy
Runs autonomously
Sends
  • writes to → Tool A
  • writes to → Tool B
Receives
  • directs ← Human operator
ResourceTool A
Tool
Tool A
Autonomy
Runs autonomously
Receives
  • writes to ← Agent
ResourceTool B
Tool
Tool B
Autonomy
Runs autonomously
Receives
  • writes to ← Agent

How a typical Solo + Tools team handles a task

Typical Solo + Tools layout — schematic, not verified wiring

  1. Task arrives

    Human operator directs Agent.

  2. Agent builds the work

    Agent builds the work.

  3. The artifact lands

    The artifact lands in Tool A: Agent contributes via "writes to". The artifact lands in Tool B: Agent contributes via "writes to".

  4. Human holds the last word

    Human operator holds final approval.

Replicate a typical Solo + Tools setup

Typical Solo + Tools layout — schematic, not verified wiring

Ingredients

  • HumanHuman operator
  • BuilderAgent
  • ResourceTool A
  • ResourceTool B

Setup order

  1. 1.Provision the substrate: Tool A and Tool B.
  2. 2.Wire Agent: it receives "directs" from Human operator.
  3. 3.Declare the human gate: Human operator holds final approval.
🐍
smolagents CodeAgentCodeAgent

smolagents (Python)

[unknown]

Performance metrics

Windowed metrics with provenance. [unknown] means it was not tracked — an honest hole beats an invented figure.

Agent logic lines of code
1,000
evidence-linked

~1000 lines: "The logic for agents fits in ~thousand lines of code." Source: huggingface.co/docs/smolagents [evidence_linked]

as of Jan 1, 2025
Benchmark task success ratenot estimated
[unknown]
evidence-linkedwhy?

No standardized benchmark figures stated on HuggingFace smolagents docs at time of indexing.

as of Jan 1, 2025

Token economics

Cost transparency is part of the honesty architecture. [unknown] means it was not tracked — not that it is zero.

No cost metrics on record. Cost tracking is hard across runtimes; honest absence beats invented figures.

Blueprint

Operational DNA — why it works, how it was built, and how it is overseen. Not files for sale; knowledge of the design.

Why it works

Python-as-actions reduces the translation overhead between LM output and execution. Minimal library size (~1K lines) keeps the framework auditable and hackable. Broad provider support avoids vendor lock-in. MCP compatibility connects to an expanding ecosystem of tools without custom integration work.

How it was built

Python package (pip install smolagents). Agents defined with a model (any provider) and a list of tools. CodeAgent produces Python blobs; ToolCallingAgent produces JSON tool calls. Multi-agent: pass agent instances wrapped in ManagedAgent to the tools list of a coordinator. Tutorial notebooks in the docs.

Oversight model

User controls model selection and tool access. Library is minimal by design — ~1K lines — to maximize auditability. Sandboxed code execution recommended for production deployments. Source: smolagents docs.

Proof (1)

The team's shared track record — tasks, incidents, lessons, milestones. Per-entry provenance tags are always visible.

  1. ArtifactJan 1, 2025evidence-linked

    smolagents CodeAgent documented in Hugging Face docs

    CodeAgent writes Python as actions rather than JSON tool calls. ~1000-line core library. Supports HuggingFace, OpenAI, Anthropic, LiteLLM, Transformers, Ollama. MCP and LangChain tool integration.

    https://huggingface.co/docs/smolagents/en/index

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